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The document states that business data from ChatGPT Business, ChatGPT Enterprise, ChatGPT for Healthcare, ChatGPT Edu, ChatGPT for Teachers, and the API Platform is not used for model training by default, and that model training use of business data requires explicit customer opt-in.
This analysis describes what OpenAI's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
This provision establishes a default data-use boundary relevant to enterprise data governance, distinguishing enterprise service tiers from consumer-facing ChatGPT products where different training data practices may apply. Compliance teams should confirm that opt-in mechanisms within their deployed workspaces are configured in accordance with organizational data policies.
The updated terms state that workspace admins 'can control' data retention rather than directly controlling it. This conditional phrasing may suggest that retention control is optional or contingent rather than a guaranteed capability. Enterprise customers relying on admin-driven data retention policies should clarify with OpenAI whether this change affects their ability to set specific retention timelines for workspace data.
View change record →The updated terms shift governance of conversation access and retention from end users to workspace administrators. Under the revised policy, workspace admins can now view, access, export, and delete any end user conversations within their workspace and control how long workspace data is retained. Additionally, OpenAI now reserves the right to retain deleted or unsaved conversations beyond the standard 30-day deletion window if retention is reasonably necessary to protect its services or any third party from harm, beyond prior language that limited retention extensions to legal requirements. Within an enterprise account, end users no longer have unilateral control over conversation visibility or deletion of their own conversations.
View change record →Current version adds explicit clarification that opted-in feedback data may be used for model training, introducing a conditional exception to the default no-training policy.
View full change record →Under this provision, business data submitted across the covered enterprise services is not used to train OpenAI models unless the customer has explicitly opted in through a disclosed mechanism. The agreement requires explicit affirmative action for model training use of business data rather than applying it by default.
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"By default, we do not use your business data for training our models. If you have explicitly opted in to share your data with us (for example, through our opt-in feedback mechanisms) to improve our services, then we may use the shared data to train our models.Excerpt from OpenAI's Enterprise Privacy
(1) REGULATORY LANDSCAPE: This provision engages GDPR principles of purpose limitation and data minimization, which require that personal data be used only for specified, explicit, and legitimate purposes. The opt-in structure disclosed here interacts with GDPR requirements around consent and legitimate interest as lawful bases for processing. The FTC Act's unfair or deceptive practices framework is also relevant to the accuracy of this commitment as made to enterprise customers. (2) GOVERNANCE EXPOSURE: Medium. The provision establishes a clear default but conditions model training use on explicit opt-in. The opt-in mechanisms referenced are described generally rather than precisely enumerated, which may create ambiguity about what actions constitute an opt-in at the workspace or user level. Legal teams should audit what workspace-level settings or user-level feedback mechanisms could trigger an opt-in. (3) JURISDICTION FLAGS: EU and UK organizations operating under GDPR should assess whether the opt-in mechanism satisfies the consent standard under GDPR if consent is the relied-upon lawful basis, and whether the DPA addresses this use restriction. California organizations should evaluate CCPA consistency if personal data of California residents is processed through the platform. (4) CONTRACT AND VENDOR IMPLICATIONS: This commitment should be verified against the executed terms of service or enterprise agreement, as the enterprise privacy page is a disclosure document rather than a standalone contract. Procurement teams should confirm that the no-training default is reflected in their DPA or enterprise agreement and is not subject to modification by a subsequent terms update without notice. (5) COMPLIANCE CONSIDERATIONS: Compliance teams should document the opt-in status of their workspace configuration, audit any feedback or data-sharing settings enabled by administrators or users, and update data processing inventories to reflect the stated exclusion of business data from model training absent opt-in.
This provision establishes a default data-use boundary relevant to enterprise data governance, distinguishing enterprise service tiers from consumer-facing ChatGPT products where different training data practices may apply. Compliance teams should confirm that opt-in mechanisms within their deployed workspaces are configured in accordance with organizational data policies.
Under this provision, business data submitted across the covered enterprise services is not used to train OpenAI models unless the customer has explicitly opted in through a disclosed mechanism. The agreement requires explicit affirmative action for model training use of business data rather than applying it by default.
No. ConductAtlas is an independent monitoring service. We are not affiliated with, endorsed by, or sponsored by OpenAI.